Bones in the vertebrate cranial base and limb skeleton grow by endochondral ossification, under the control of growth plates. Mechanisms of endochondral ossification are conserved across growth plates, which increases covariation in size and shape among bones, and in turn may lead to correlated changes in skeletal traits not under direct selection. We used micro-CT and geometric morphometrics to characterize shape changes in the cranium of the Longshanks mouse, which was selectively bred for longer tibiae. We show that Longshanks skulls became longer, flatter, and narrower in a stepwise process. Moreover, we show that these morphological changes likely resulted from developmental changes in the growth plates of the Longshanks cranial base, mirroring changes observed in its tibia. Thus, indirect and non-adaptive morphological changes can occur due to developmental overlap among distant skeletal elements, with important implications for interpreting the evolutionary history of vertebrate skeletal form.

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N=10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

Many bones in the vertebrate skeleton, including the limb bones, axial skeleton, and bones of the floor of the cranium, grow through the process of endochondral ossification, under the control of growth plates. The cellular and molecular mechanisms of endochondral ossification are conserved across these cartilaginous growth plates, increasing the tendency of skeletal elements to covary in size and shape. Covariation at the phenotypic, developmental, and genetic levels has been hypothesized to lead to correlated changes in parts of the skeleton not under direct selection. We tested this hypothesis using the selectively bred Longshanks mouse, in which the sole target of selection was relative tibia length. We use x-ray micro-computed tomography (uCT) and geometric morphometrics in a large, multi-generation sample of Longshanks and random-bred wildtype mice to characterize shape changes in the Longshanks cranium. We show that Longshanks skulls became longer, flatter, and narrower in a stepwise intergenerational process. Moreover, we show that these morphological changes likely resulted from underlying developmental changes in the growth plates of the cranial base, that mirror changes in the process of endochondral ossification observed in the Longshanks tibia growth plate. Taken together, these results show that indirect, and potentially non-adaptive, skeletal changes can occur due to developmental overlap among distant anatomical elements, with important implications for interpreting the evolutionary history of vertebrate skeletal form.

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, 10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

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